AI Lead Developer

Key Responsibilities

• Design and develop enterprise-grade Agentic AI and Generative AI solutions.
• Build multi-agent systems using LangGraph, AutoGen, ADK, MCP, and related frameworks.
• Develop RAG-based applications leveraging vector databases and enterprise knowledge sources.
• Build scalable APIs and AI microservices using Python, FastAPI, and cloud-native architectures.
• Deploy AI solutions on AWS, Azure, or GCP using Docker, Kubernetes, and CI/CD pipelines.
• Implement AI security, governance, observability, and guardrails.
• Collaborate with business, product, and engineering teams to deliver AI-driven solutions.
• Conduct code reviews, mentor engineers, and contribute to AI architecture and roadmap planning.

Required Skills

• 10+ years of software engineering experience with 4+ years in AI/GenAI solutions.
• Strong Python development experience with FastAPI or Flask.
• Hands-on experience with: LangChain LangGraph AutoGen ADK MCP (Model Context Protocol) Multi-Agent Architectures.
• Experience building RAG pipelines, embeddings, prompt engineering, and vector search solutions.
• Experience with vector databases such as Pinecone, Weaviate, FAISS, Chroma, or Azure AI Search.
• Strong knowledge of REST APIs, microservices, distributed systems, and cloud platforms (AWS/Azure/GCP).
• Experience with Docker, Kubernetes, Redis, Kafka, and AI application deployment.
• Strong understanding of AI security, memory management, scalability, and production AI systems.

Preferred Skills

• Experience with OpenAI, Azure OpenAI, Claude, Gemini, and Hugging Face models.
• Knowledge of MLOps, AI evaluation frameworks, and AI governance.
• Experience with Spark, Kafka, and large-scale AI platforms.
• Prior experience leading AI initiatives and mentoring engineering teams.